docstr: Returns the component's default config.
docstr_tok: ["Returns","the","component","'s","default","config","."]
code: def get_default_config() -> Dict[Text, Any]:
      """Returns the component's default config."""
      return {
          **SparseFeaturizer.get_default_config(),
          "analyzer": "word",
          "min_ngram": 1,
          "max_ngram": 1,
      }
  
imports: import logging
  from typing import Any, Text, Dict, List, Type
  from sklearn.feature_extraction.text import TfidfVectorizer
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.engine.graph import ExecutionContext, GraphComponent
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.nlu.featurizers.sparse_featurizer.sparse_featurizer import SparseFeaturizer
  from rasa.nlu.tokenizers.tokenizer import Tokenizer
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.training_data.features import Features
  from rasa.shared.nlu.training_data.message import Message
  from rasa.nlu.constants import DENSE_FEATURIZABLE_ATTRIBUTES, FEATURIZER_CLASS_ALIAS
  from joblib import dump, load
  from rasa.shared.nlu.constants import TEXT, TEXT_TOKENS, FEATURE_TYPE_SENTENCE, FEATURE_TYPE_SEQUENCE
label_desc: Use image node_id 3 for calling the TfIdfFeaturizer obj's underlying member method code with example usage: obj.get_default_config() and returns: dict